The diagnosis of tuberculosis (TB) is still a major challenge, especially in resource-constrained settings1. Sputum based tests are widely used to diagnose active TB, but most of these tests have serious limitations: staining for acid fast bacilli (AFB), the most widely used test, has poor sensitivity2. Bacterial culture from sputum remains the gold standard method for TB diagnosis, but might fail to deliver results in a time effective manner. The automated real-time sputum processing molecular beacon assay, XpertMTB/RIF assay (Cepheid Inc., CA, USA) yields results within 2 hours with high sensitivity and specificity (98-100%) in smear positive cases, but only moderate sensitivity (68-72%) in smear negative TB cases2. Cost effectiveness of the GeneXpert test remains one of the major impediments to the large-scale roll-out of the test in high burden but resource-constrained settings. Furthermore, sputum based tests (including the GeneXpert) have limited clinical utility in individuals with difficulty in providing good quality sputum samples, such as children and those with extra pulmonary TB disease. Immunological tests may be beneficial in such cases (especially if they are developed into rapid, point-of-care tests). However, serological tests have shown high variability—sensitivity between 10% and 90% and specificity between 47% and 100%5—and therefore have limited utility clinically and have been prohibited by the WHO11.
T-cell based immunological assays such as the interferon gamma (IFN-γ) release assays (IGRAs) added a new value to immunological diagnosis of TB, especially when compared to the traditional skin test (TST)12. This is due to the use of highly immunogenic Mycobacterium tuberculosis (M.tb) specific antigens: the 6-kDa early secretory antigenic target (ESAT-6), 10-kDa culture filtrate protein (CFP-10) and TB7.7 (Rv2654), the latter only being used in the Quantiferon TB Gold In Tube (QFT-IT) test. However, IGRAs do not differentiate between active TB disease and latent M.tb infection and although useful in low incidence settings, they are not recommended for high burden settings and therefore only used for research purposes in high burden areas26.
There is therefore a need for a method for diagnosing TB disease, which will be suitable for use in resource limited settings and which can distinguish between latent infection and active disease.